RNAseq toolbox
From BITS wiki
Contents
- 1 Complete graphical analysis packages
- 2 Experimental design
- 3 Quality control and visualization of raw reads
- 4 Preprocessing of reads
- 5 Aligning of RNA-seq reads
- 6 Quality control of alignment
- 7 Assembly of RNA-seq reads
- 8 Expression analysis
- 9 Splicing/isoform detection and analysis
- 10 Combination with gene expression microarray data
- 11 References
Complete graphical analysis packages
- SeqMonk - Brabaham institute
- MeV - Dana-Farber Cancer Institute
- GenePattern - Broad institute
- RNA-eXpress - Monash University
- Rockhopper - Focused on NGS from bacterial species
- GobyWeb - Webportal for frequent data analyses for RNA-Seq, Methyl-Seq, RRBS, or DNA-Seq
- Galaxy - Webframework for performing reproducible and shareable bioinformatics analysis, with tools for NGS
- RobiNA - A Java GUI ([1]) that supports analysis of MA data (single and two colors), as well as RNASeq analysis using EdgeR and DESeq. This is a very easy to use program that will generate a DE table in no time and perform some QC as well on your data (a must for people in a hurry).
- RNASeqGUI ([2]) - will drive a number of Bioconductor packages to perform the actual analysis. You will still need to install a bunch of packages once under [R] but will after that benefit from the GUI to run your analyses (link to the PDF manual). The current version uses methods from the following packages: EdgeR, DESeq, DESeq2, NOISeq, and baySeq. Additional tools are required to annotate the data and run the graphical environment; it also uses multiple cores when this is possible to speed up the analysis.
Experimental design
- UOregon RNA-seq Guide - Very helpful and nicely structured website on setting up your experiment
- Scotty - Web tool for Designing RNA-Seq Experiments to Measure Differential Gene Expression
- SSPA - R package for general Sample size and power analysis for microarray and next-generation sequencing data.
- RNASeqPower - R package for sample size selection for RNAseq studies
Quality control and visualization of raw reads
- Picard tools - JAVA command line
- FastQC - JAVA graphical
- qrqc - Bioconductor
- PrinSeq
Background info
Preprocessing of reads
Removing biological and technical contamination.
- ncproseq - determining amount of ncRNA
- Sickle - trimming based on windowed quality scores
- Scythe - a very simple adapter trimmer
- Trimmomatic - Trimming of adapters and contamination
- CutAdapt - Removal of adapter sequences
- ea-utils - Command line and Galaxy.
- PrinSeq - (note: it is Particularly designed for 454/Roche data, but can be applied on Illumina also)
Aligning of RNA-seq reads
See also the general mappers page
- Bowtie2 - to a reference genome
- TopHat2 - to a reference genome
- GSNAP - to a reference genome
- RNASEQR - to a reference genome (L. Hood, ISB)
- RNASTAR - to a reference genome, extremely fast
- RSEM - Mapping RNA-seq reads to the transcriptome
- CRAC
- MapSplice - mapping for splice junction discovery
Remapping with updated annotations
This tool takes an alignment performed earlier and remaps and recounts based on new annotation files. On large sets, this saves time.
- ReXpress - Remapping and recounting based on updated annotations
Quality control of alignment
- Qualimap - graphical and command line
- RNA-SeQC - JAVA command line
- Picard tools - command line, also available in Galaxy (version!)
- RSeQC - Baylor
- GeneScissors - Analysis of misalignment by machine learning
Assembly of RNA-seq reads
Assembly
Mapping-first techniques
- Cufflinks - Assembles and estimates relative expression rates, relies on a reference genome
- Scripture - relies on RNA-Seq reads and an assembled reference genome
- CEM - Assembles and estimates isoforms, including expression level estimation
- ERANGE
De novo or assembly-first techniques
- Trinity - Broad Institute
- SOAPdenovo-Trans - de novo transcriptome assembler by BGI, taking into account PE reads
- Oases - transcriptome assembler for very short reads
- Mira - Capable of assembling reads of different platforms
- EBARDenovo - resolving sequencing errors, repetitive sequences and aberrant chimeric amplicons.
- Trans-Abyss - Assembler taking into account PE reads
- Phusion assembler - Broad Institute
- Newbler - This is the assembler of Roche 454
- Celera Assembler - de novo whole-genome shotgun (WGS) DNA sequence assembler.
Not maintained
- Velvet - EBI's assembler for very short reads
Mapping assembled transcriptomes to reference genome sequence
- NucMer from the Mummer package
- BLAT - BLAST-like alignment tool
- GMAP - Mapping and Aligning mRNA and EST Sequences to genomes
- Exonerate - In the est2genome mode
Mapping reads to assembled transcriptomes
Basically, any gap-free aligner will do.
Expression analysis
Feature counting
- HTSeq - Commandline (also part of the DNAseq toolbox)
- Qualimap - Graphical and command line
- GenomicRanges summarizeOverlaps - Bioconductor package - Create_a_count_table_in_R
- EDGE-Pro - Mapping and counting feature in Prokaryotic genomes
- easyRNASeq - Bioconductor package -
- RSEM - rsem-calculate-expression (after aligning to transcriptome)
- CuffLinks
- rQuant - not maintained
- IsoEM - not maintained
Quality control of samples
- SERE - SERE is a statistic computed from the count table, to check replicates and conditions. See the code to compute SERE
Count normalisation methods
- TMM - Trimmed Mean of M-values
- RLE
- Upper Quartile
- Total counts (fractions)
- Peak of histogram normalization
- VST - Variance Stabilizing transformation - See documentation DESeq
Detecting differential expression by count analysis
- edgeR - DE on the gene level from counts - TOP
- DEseq - DE on the gene level from counts - TOP
- tweeDEseq - DE on the gene level from counts
- NBPSeq - DE on the gene level from counts
- TSPM - DE on the gene level from counts
- SAMseq - non-parametric method on the gene level from counts - TOP if large number of replicates
- ShrinkSeq - DE on the gene level from counts
- BBSeq - DE on the gene level
- Bayseq - DE on the gene level from counts - TOP
- DEGseq - DE on the gene level
- sydSeq - improved DE on the gene level for low replicate studies
- DEXSeq - DE on the exon level
- NOIseq - Non-parametric method from counts
- CuffLinks cuffdiff2 - DE on the isoform level - TOP
- BitSeq - DE on the isoform level
- EBSeq - DE on the isoform level from counts
- Myrna - cloud computing for large RNA-seq datasets
- sSeq - optimized for small sample size experiments.
- MRFSeq - optimized for small read counts
- QuasiSeq - apply the QL, QLShrink and QLSpline methods to RNA-seq data for DE
Time series analysis
Methodology
RNA-seq specific gene set analysis
- SeqGSEA (R) - Gene set analysis with taking into account DE and splicing
Splicing/isoform detection and analysis
- CuffLinks - Detection of isoforms and quantification.
- DSGseq - identifying differentially spliced genes from two groups of RNA-seq samples
- FusionHunter - detection of fused transcripts
- iReckon - splice detection with abundance estimation
- DiffSplice - detection of differential splicing events
- ASprofile - extracting, quantifying and comparing alternative splicing
- IQSeq - Integrated Isoform Quantification Analysis
- IsoEM - Infer isoform and gene expression levels
- Splicing Compass - Predict differentially spliced genes between two different conditions
- rDiff - detect changes of the RNA processing between two samples
- Solas - quantification of alternative splice forms in a single condition
- CEM - Assembles and estimates isoforms, including expression level estimation
- Montebello - Isoform discovery [1]
- MISO - Identifying isoform regulation
- NURD - inference isoform expression
- Barnacle - detecting and characterizing chimeric transcripts from long RNA sequences, such as those generated by de novo transcriptome assembly
Combination with gene expression microarray data
- PREBS - R package to make RNA-seq results comparable to MA results
References
Evaluating differential expression detection algorithms
- Xu et al. 2013
- Kvam et al. 2012
- Wesolowski et al. 2013
- Soneson & Delorenzi 2013
- Rapaport et al. 2013
- Reeb & Steibel - 2013
Differential expression analysis tutorials
References:
- ↑
Marc Lohse, Anthony M Bolger, Axel Nagel, Alisdair R Fernie, John E Lunn, Mark Stitt, Björn Usadel
RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics.
Nucleic Acids Res: 2012, 40(Web Server issue);W622-7
[PubMed:22684630] ##WORLDCAT## [DOI] (I p) - ↑
Francesco Russo, Claudia Angelini
RNASeqGUI: a GUI for analysing RNA-Seq data.
Bioinformatics: 2014, 30(17);2514-6
[PubMed:24812338] ##WORLDCAT## [DOI] (I p)
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